ESHG 2014: The role of population isolates in understanding genetic and complex diseases

Title: S08.3 - The role of population isolates in understanding genetic and complex diseases
Keywords: genetic isolates; complex and quantitative traits; genetic diseases
Authors: P. Gasparini; Trieste, Italy.

Abstract: The use of isolated populations to reduce disease heterogeneity of complex disorders has already proven very useful in identifying DNA polymorphisms associated with complex diseases and quantitative traits. The study of complex traits in geographically and culturally isolated populations is particularly useful because the entire population can be analyzed, the relative weight of environmental variation can be controlled and genetic factors can be more easily identified. In these genetically and culturally homogeneous populations, a large proportion of individuals presenting a given trait is likely to share the same trait-predisposing gene inherited from a common ancestor. Furthermore, inbreeding, typical of small communities, reduces genetic heterogeneity and increases homozygosity, providing greater power for detection of susceptibility genes. We have created the Italian Network of Genetic Isolates (INGI) that collects the samples coming from several villages from 5 different Italian regions for a total of more than 6000 samples. Moreover, additional 1500 samples have been collected along the Silk Road. For all of them a great number of information regarding medical records, hematological parameters and lifestyle has been collected as well as DNA samples which have been genotyped with high density chip arrays. To evaluate the power to detect association in our cohorts we aimed at replicating several already published results and to verify if any new Italian specific loci were present. For example, GWAS were carried out on several hematological and serum lipids traits, blood glucose levels, blood pressure and anthropometric measures leading to the replication of 206 loci and to the discovery of some novel associations for BMI and weight. For 12 of these loci the top associated SNP was different from the one previously published highlighting the importance of having a population specific reference panel for personalized medicine. Moreover, specific genes/variants associated to phenotypes such as hearing, smell, taste and food preferences have been identified. More recently, new data have been obtained using whole genome sequencing data that allow refining the results previously obtained and will lead to the discovery of even more population specific genetic variants. Our results show that genetic isolates are a powerful resource for studying complex traits and thus to create genetic risk profiles which will be the bases for personalized medicine in Italy. Updated data will be presented and discussed.

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